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Special Issue on Science-Driven Cloud Computing

Ivona Brandic, Ioan Raicu
2011 Scientific Programming  
Are there scientific HPC/HTC/MTC workloads that are suitable candidates to take advantage of emerging cloud computing resources with high efficiency?  ...  on using many computing resources over long periods of time to accomplish its computational tasks, many-task computing (MTC) which aims to bridge the gap between HPC and HTC by focusing on using many  ... 
doi:10.1155/2011/362493 fatcat:lknlfqvmevc3xovxzjd5jep6kq

HEP-Frame: A Software Engineered Framework to Aid the Development and Efficient Multicore Execution of Scientific Code

Andre Pereira, Antonio Onofre, Alberto Proenca
2015 2015 International Conference on Computational Science and Computational Intelligence (CSCI)  
a wide set of multicore systems, with both HPC and HTC techniques.  ...  HEP-Frame is the result of a tight collaboration between computational scientists and software engineers: it aims to improve scientists coding productivity, ensuring an efficient parallel execution on  ...  This goal compels computational scientists to give higher priority to the efficiency of their scientific code on any computing platform, applying a merge of HPC and HTC techniques without compromising  ... 
doi:10.1109/csci.2015.42 fatcat:64a3dcpaozcptlcrolqpkvngk4

Many-task computing for grids and supercomputers

Ioan Raicu, Ian T. Foster, Yong Zhao
2008 2008 Workshop on Many-Task Computing on Grids and Supercomputers  
Many-task computing aims to bridge the gap between two computing paradigms, high throughput computing and high performance computing.  ...  both dependent and independent tasks), where primary metrics are measured in seconds (e.g.  ...  of Advanced Scientific Computing Research, Office of Science, U.S.  ... 
doi:10.1109/mtags.2008.4777912 dblp:conf/sc/RaicuFZ08 fatcat:u3fyhpolcrav7ggrmrgron4qja

Techniques and tools for measuring energy efficiency of scientific software applications [article]

David Abdurachmanov, Peter Elmer, Giulio Eulisse, Robert Knight, Tapio Niemi, Jukka K. Nurminen, Filip Nyback, Goncalo Pestana, Zhonghong Ou, Kashif Khan
2014 arXiv   pre-print
The scale of scientific High Performance Computing (HPC) and High Throughput Computing (HTC) has increased significantly in recent years, and is becoming sensitive to total energy use and cost.  ...  Energy-efficiency has thus become an important concern in scientific fields such as High Energy Physics (HEP).  ...  ARMv8 and energy profiling support in IgProf was also supported by Google Summer of Code (GSoC 2014).  ... 
arXiv:1410.3440v1 fatcat:uvmaqmw7gvbc3db3gse2uwmnj4

Techniques and tools for measuring energy efficiency of scientific software applications

David Abdurachmanov, Peter Elmer, Giulio Eulisse, Robert Knight, Tapio Niemi, Jukka K Nurminen, Filip Nyback, Gonçalo Pestana, Zhonghong Ou, Kashif Khan
2015 Journal of Physics, Conference Series  
The scale of scientific High Performance Computing (HPC) and High Throughput Computing (HTC) has increased significantly in recent years, and is becoming sensitive to total energy use and cost.  ...  Energy-efficiency has thus become an important concern in scientific fields such as High Energy Physics (HEP).  ...  Data processing and storage are distributed across the Worldwide LHC Computing Grid (WLCG) [2] , which uses resources from 160 computer centers in 35 countries.  ... 
doi:10.1088/1742-6596/608/1/012032 fatcat:n24zh22uh5fs3nwjhe6d3wvz5q

Effects of Dynamic Voltage and Frequency Scaling on a K20 GPU

Rong Ge, Ryan Vogt, Jahangir Majumder, Arif Alam, Martin Burtscher, Ziliang Zong
2013 2013 42nd International Conference on Parallel Processing  
Improving energy efficiency is an ongoing challenge in HPC because of the ever-increasing need for performance coupled with power and economic constraints.  ...  In this paper, we experimentally study the impacts of DVFS on application performance and energy efficiency for GPU computing and compare them with those of DVFS for CPU computing.  ...  CONCLUSIONS In this paper, we experimentally study the effects of CPU and GPU DVFS on the performance and energy efficiency of scientific workloads on a GPU-accelerated heterogeneous system built upon  ... 
doi:10.1109/icpp.2013.98 dblp:conf/icpp/GeVMABZ13 fatcat:67qusfuuq5gvbmsaxn73p3r2he

Guest Editors' Introduction: Special Section on Many-Task Computing

Ioan Raicu, Ian T. Foster, Yong Zhao
2011 IEEE Transactions on Parallel and Distributed Systems  
We introduce the term many-task computing (MTC) [2] for computations that bridge the gap between high-performance computing (HPC) and high-throughput computing (HTC) [1] .  ...  MTC differs from HTC in its emphasis on using many computing resources over short periods of time to accomplish many computational tasks (both dependent and independent), for which primary metrics are  ...  ACKNOWLEDGMENTS This work was supported in part by the US Department of Energy (DOE) under Contract DE-AC02-06CH11357 and the US National Science Foundation grant NSF-0937060 CIF-72.  ... 
doi:10.1109/tpds.2011.138 fatcat:zfnwm7fmuvefbimbgeg2zsaqn4

EGI-ACE D2.5 EOSC Compute Platform Handbook

G. La Rocca, G. Sipos, E. Fernández, L. Farkas, A. Manzi, A. Cristofori
2022 Zenodo  
The EOSC Compute Platform (ECP) is a system of federated compute and storage facilities together with higher-level platforms to support various data and application hosting, data processing, and analysis  ...  The EOSC Compute Platform Handbook is written for EOSC users to provide guidance on how to use the various services of the EOSC Compute Platform.  ...  Cloud, HTC and HPC).  ... 
doi:10.5281/zenodo.6396444 fatcat:fsjehohof5ahnn5jyhsjngzouu

Towards an HPC Complementary Computing Facility [article]

K. Herner, M. Kirby, S. Timm
2022 arXiv   pre-print
This Letter considers the design for computing facilities that are complementary to the leadership class High Performance Computing (HPC) facilities.  ...  facility, as well as the services needed to provide computing for workflows that are not a good fit for the HPC facilities.  ...  At the same time, considerable development is necessary in order to transition from current HTC computing models and to efficiently access resources at LCFs.  ... 
arXiv:2203.08861v1 fatcat:t4gcl6zqx5g4lab4bwdr3drmou

EGI-ACE D2.5 EOSC Compute Platform Handbook

G. La Rocca, G. Sipos, E. Fernández, L. Farkas, A. Manzi, A. Cristofori
2022 Zenodo  
The EOSC Compute Platform (ECP) is a system of federated compute and storage facilities together with higher-level platforms to support various data and application hosting, data processing, and analysis  ...  The EOSC Compute Platform Handbook is written for EOSC users to provide guidance on how to use the various services of the EOSC Compute Platform.  ...  Compute running computational jobs at by splitting the data into small pieces, EGI's Workload Manager 119 is a service that provides efficient management and distribution of workloads on the distributed  ... 
doi:10.5281/zenodo.6602248 fatcat:r3ynjtd5xffn5ni45lywpofwgq

EGI-ACE D2.3 Technical specifications for compute common services

Enol Fernández, Gergely Sipos, Marica Antonacci, Valeria Ardizzone, Priyasma Bhoumik, Miguel Caballer, Amanda Calatrava, Ian Collier, Rose Cooper, William Karageorgos, Bartosz Kryza, Nicolas Liampotis (+11 others)
2021 Zenodo  
tools to facilitate the execution of workloads in the distributed infrastructure.  ...  EGI-ACE builds on the computing e-Infrastructure of the EGI Federation to deliver the EOSC Compute Platform: an open, data-centric, distributed, hybrid and secure infrastructure consisting of computing  ...  Workload Manager The Workload Manager Service (WMS) dispatches user's computing tasks in an efficient way while maximising the usage of distributed computational resources.  ... 
doi:10.5281/zenodo.6602270 fatcat:co7eycltenblflscxlth2l4sra

D7.7: Hardware developments IV

Alan Ó Cais, Jony Castagna, Godehard Sutmann
2019 Zenodo  
Update on "Hardware Developments III" (Deliverable 7.5: https://doi.org/10.5281/zenodo.1304088) which covers: - Report on hardware developments that will affect the scientific areas of interest to E-CAM  ...  platforms; and, - detailed output from direct face-to-face session between the project endusers, developers and hardware vendors.  ...  Silicon is being dedicated to deep learning workloads and the scientific workloads for these products will need to adapt to leverage this silicon.  ... 
doi:10.5281/zenodo.3256136 fatcat:hfpwvelb3zdxlk6fmkgddqgqoq

D7.9: Hardware developments V

Alan O'Cais, Christopher Werner, Simon Wong, Padraig Ó Conbhuí, Jony Castagna, Godehard Sutmann
2020 Zenodo  
Update on "Hardware Developments IV" (Deliverable 7.7: https://doi.org/10.5281/zenodo.3256137) which covers: - Report on hardware developments that will affect the scientific areas of interest to E-CAM  ...  platforms; and, - detailed output from direct face-to-face session between the project endusers, developers and hardware vendors.  ...  NVidia has just released the new GPU architecture, Ampere, which contains a higher mix of CUDA cores (for compute workloads), Tensor Cores (for AI and Deep Learning workloads, and now even in full FP32  ... 
doi:10.5281/zenodo.3931510 fatcat:kelxr6ap5vfunpjisfpwiauwue

Executing dynamic heterogeneous workloads on Blue Waters with RADICAL-Pilot

Mark Santcroos, Ralph Castain, Andre Merzky, Iain Bethune, Shantenu Jha
2016 Zenodo  
In this paper we describe the design and characterize the performance of its RADICAL-Pilot's scheduling and executing components on Crays, which are engineered for efficient resource utilization while  ...  These workloads can benefit from being executed at scale on HPC resources, but a tension exists between the workloads' resource utilization requirements and the capabilities of the HPC system software  ...  This research is part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (awards OCI-0725070 and ACI-1238993) and the state of Illinois.  ... 
doi:10.5281/zenodo.3373740 fatcat:psmiyicmxjcsrhms6mr7vuwmgi

EGI-ACE D2.3 Technical specifications for compute common services

Enol Fernández, Gergely Sipos, Marica Antonacci, Valeria Ardizzone, Priyasma Bhoumik, Miguel Caballer, Amanda Calatrava, Ian Collier, Rose Cooper, William Karageorgos, Bartosz Kryza, Nicolas Liampotis (+11 others)
2021 Zenodo  
tools to facilitate the execution of workloads in the distributed infrastructure.  ...  EGI-ACE builds on the computing e-Infrastructure of the EGI Federation to deliver the EOSC Compute Platform: an open, data-centric, distributed, hybrid and secure infrastructure consisting of computing  ...  Workload Manager The Workload Manager Service (WMS) dispatches user's computing tasks in an efficient way while maximising the usage of distributed computational resources.  ... 
doi:10.5281/zenodo.5526125 fatcat:adyvqwxw7bdjhbq3dt3b7ehvki
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